code: def finetuning_model(model: Module):
      optimizer = torch.optim.SGD(
          model.parameters(), lr=0.01, momentum=0.9, weight_decay=5e-4
      )
      training_model(model, optimizer, F.nll_loss)
  
file_path: nni/test/algo/compression/assets/simple_mnist/simple_torch_model.py
imports: from __future__ import annotations
  from typing import Callable, Tuple
  import torch
  from torch.nn import Module
  import torch.nn.functional
  from torch.optim import Optimizer
  from torch.utils.data import DataLoader
  from torchvision.datasets import MNIST
  from torchvision import transforms
  from ..device import device
  from nni.common.types import SCHEDULER
label_desc: Use image node_id 3 for calling a global function with example usage: finetuning_model(model) without return types